System information (for reproducibility):
Julia Version 1.10.2
Commit bd47eca2c8a (2024-03-01 10:14 UTC)
Build Info:
Official https://julialang.org/ release
Platform Info:
OS: macOS (arm64-apple-darwin22.4.0)
CPU: 12 × Apple M2 Max
WORD_SIZE: 64
LIBM: libopenlibm
LLVM: libLLVM-15.0.7 (ORCJIT, apple-m1)
Threads: 8 default, 0 interactive, 4 GC (on 8 virtual cores)
Environment:
JULIA_NUM_THREADS = 8
JULIA_EDITOR = code
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Load packages:
using Pkg Pkg .activate (pwd ())Pkg .instantiate ()Pkg .status ()
Activating project at `~/Documents/github.com/ucla-biostat-257/2024spring/slides/04-juliaplot`
Status `~/Documents/github.com/ucla-biostat-257/2024spring/slides/04-juliaplot/Project.toml`
[c91e804a] Gadfly v1.4.0
[f0f68f2c] PlotlyJS v0.18.13
[91a5bcdd] Plots v1.40.3
[d330b81b] PyPlot v2.11.2
[6f49c342] RCall v0.14.1
[9a3f8284] Random
using Gadfly , Plots , PlotlyJS , PyPlot , Random , RCall
Plotting in Julia
The popular options (currently) for plotting in Julia are:
Gadfly.jl
To demonstrate Gadfly, we will go through an example and compare it to ggplot2.
using RCall """ library(ggplot2) library(dplyr) df <- ToothGrowth %>% group_by(supp, dose) %>% summarise(se = sd(len) / n(), len = mean(len), n = n()) ggplot(df, aes(x = dose, y = len, group = supp, color = supp)) + geom_line() + geom_point() + geom_errorbar(aes(ymin = len - se, ymax = len + se), width = 0.1, alpha = 0.5, position = position_dodge(0.005)) + scale_color_manual(values = c(VC = "skyblue", OJ = "orange")) + labs(x = "Dose", y = "Tooth Length") """
┌ Warning: RCall.jl: `summarise()` has grouped output by 'supp'. You can override using the
│ `.groups` argument.
└ @ RCall /Users/huazhou/.julia/packages/RCall/dDAVd/src/io.jl:172
@rget df # retrieve dataframe from R to Julia workspace using Gadfly : ymin] = df[!, : len] - df[!, : se]: ymax] = df[!, : len] + df[!, : se]plot (df, = : dose, = : len, = : supp, xlabel ("Dose" ), ylabel ("Tooth Length" ), xticks (ticks = [0.5 , 1.0 , 1.5 , 2.0 ]),= : ymin, = : ymax, color_discrete_manual ("orange" , "skyblue" ))
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2.0,26.14
1.0,16.77
0.57.9799999999999995
2.0,26.06
1.0,22.7
0.5,13.23
h,j,k,l,arrows,drag to pan
i,o,+,-,scroll,shift-drag to zoom
r,dbl-click to reset
c for coordinates
? for help
?
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Both offer more customized options
""" ggplot(df, aes(x = dose, y = len, group = supp, color = supp)) + geom_line() + geom_point() + geom_errorbar(aes(ymin = len - se, ymax = len + se), width = 0.1, alpha = 0.5, position = position_dodge(0.005)) + theme(legend.position = c(0.8,0.1), legend.key = element_blank(), axis.text.x = element_text(angle = 0, size = 11), axis.ticks = element_blank(), panel.grid.major = element_blank(), legend.text=element_text(size = 11), panel.border = element_blank(), panel.grid.minor = element_blank(), panel.background = element_blank(), axis.line = element_line(color = 'black',size = 0.3), plot.title = element_text(hjust = 0.5)) + scale_color_manual(values = c(VC = "skyblue", OJ = "orange")) + labs(x = "Dose", y = "Tooth Length") """
plot (df, x = : dose, y = : len, color = : supp, Geom.point,xlabel ("Dose" ), Guide.ylabel ("Tooth Length" ), xticks (ticks = [0.5 , 1.0 , 1.5 , 2.0 ]),Theme (panel_fill = nothing , highlight_width = 0 mm, point_size = 0.5 mm,= : inside, = 0 mm, panel_stroke = colorant"black" ),= : ymin, ymax = : ymax, color_discrete_manual ("orange" , "skyblue" ))
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0.5
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1.5
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2.0,26.14
1.0,16.77
0.57.9799999999999995
2.0,26.06
1.0,22.7
0.5,13.23
OJ
VC
supp
h,j,k,l,arrows,drag to pan
i,o,+,-,scroll,shift-drag to zoom
r,dbl-click to reset
c for coordinates
? for help
?
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Plots.jl
We demonstrate Plots.jl below:
# Pkg.add("Plots") using Plots , Random Random .seed! (123 ) # set seed = cumsum (randn (50 , 2 ), dims= 1 );
# Pkg.add("PyPlot") pyplot () # set the backend to PyPlot plot (x, title= "Random walk" , xlab= "time" )
gr () # change backend to GR plot (x, title= "Random walk" , xlab= "time" )
gr()
@gif for i in 1:20
Plots.plot(x -> sin(x) / (.2i), 0, i, xlim=(0, 20), ylim=(-.75, .75))
scatter!(x -> cos(x) * .01 * i, 0, i, m=1)
end;produces following animation.
# Pkg.add("PlotlyJS") plotlyjs () # change backend to PlotlyJS plot (x, title= "Random walk" , xlab= "time" )
